Package 'epiextractr'

Description

Returns file paths for the specified CPS sample and years. Useful for targets-based workflows where file dependencies need to be tracked. The result can be passed directly to load_cps() or the load_org(), load_basic(), etc. wrappers in place of .years.

Usage

cps_files(
  sample,
  years,
  extracts_dir = NULL,
  .quiet = getOption("epiextractr.quiet", FALSE)
)

Arguments

Value

A character vector of file paths

Examples

cps_files("org_sample", 2023:2025)

# Pass directly to load functions:
load_org_sample(cps_files("org_sample", 2023:2025), year, month, wage)

## Not run: 
# Use with targets
library(tarchetypes)
tar_assign({
  org_files = cps_files("org", 2020:2025) |> tar_file()
  org_data = load_org(org_files, year, month, wage) |> tar_target()
})

## End(Not run)

Description

Retrieve metadata from CPS extract

Usage

cps_version(x)

cps_citation(x)

assert_cps_version(x, version)

Arguments

Value

cps_version and cps_citation return version or citation strings.

assert_cps_version returns an error when the provided version is incorrect.

Examples

cps_org <- load_org_sample(2023:2025)
cps_citation(cps_org)
cps_version(cps_org)

Description

Download the EPI CPS extracts to your local machine

Usage

download_cps(sample, extracts_dir = NULL, overwrite = FALSE)

Arguments

Value

downloaded files

Examples

## Not run: 
download_cps(sample = "march", extracts_dir = "/data/cps")

## End(Not run)

Description

Select years and variables from the EPI CPS microdata extracts. These data must first be downloaded using download_cps() or from https://microdata.epi.org.

Usage

load_cps(
  .sample,
  .years,
  ...,
  .extracts_dir = NULL,
  .version_check = TRUE,
  .quiet = getOption("epiextractr.quiet", FALSE)
)

load_basic(
  .years,
  ...,
  .extracts_dir = NULL,
  .version_check = TRUE,
  .quiet = getOption("epiextractr.quiet", FALSE)
)

load_may(
  .years,
  ...,
  .extracts_dir = NULL,
  .version_check = TRUE,
  .quiet = getOption("epiextractr.quiet", FALSE)
)

load_org(
  .years,
  ...,
  .extracts_dir = NULL,
  .version_check = TRUE,
  .quiet = getOption("epiextractr.quiet", FALSE)
)

load_org_sample(
  .years,
  ...,
  .extracts_dir = NULL,
  .version_check = TRUE,
  .quiet = getOption("epiextractr.quiet", FALSE)
)

Arguments

Details

All columns are selected if ... is missing.

.years accepts either integer years or file paths from cps_files(). When file paths are passed, the files are read directly and .extracts_dir is ignored.

.extracts_dir is required, but if NULL it will look for the environment variables

EPIEXTRACTS_CPSBASIC_DIR
EPIEXTRACTS_CPSORG_DIR
EPIEXTRACTS_CPSMAY_DIR

which could be set in your .Renviron, for example.

Value

A tibble of CPS microdata

Functions

• load_cps(): base function group

• load_basic(): Load CPS Basic Monthly files

• load_may(): Load CPS May files

• load_org(): Load CPS ORG files

• load_org_sample(): Load a demonstration sample of CPS ORG files; only useful for examples

Examples

# Load all columns from the demonstration sample
load_org_sample(2023:2024)

# Load a selection of columns
load_org_sample(2023:2025, year, month, female, wage)

# Use cps_files() for targets workflows:
org_files = cps_files("org_sample", 2023:2025)
load_org_sample(org_files, year, month, wage)

## Not run: 
# Load real CPS ORG data (requires downloaded extracts):
load_org(2010:2019, year, month, orgwgt, female, wage)
# This is equivalent to
load_cps("org", 2010:2019, year, month, orgwgt, female, wage)

## End(Not run)